A novel weighted TPR-TNR measure to assess performance of the classifiers

Ali, 2017, Accurate multi-criteria decision making methodology for recommending machine learning algorithm, Expert Systems with Applications, 71, 257, 10.1016/j.eswa.2016.11.034 Behzadian, 2012, A state-of the-art survey of TOPSIS applications, Expert Systems with Applications, 39, 13051, 10.1016/j.eswa.2012.05.056 Brazdil, 2000, A comparison of ranking methods for classification algorithm selection, 63 Brown, 2012, An experimental comparison of classification algorithms for imbalanced credit scoring data sets, Expert Systems with Applications, 39, 3446, 10.1016/j.eswa.2011.09.033 Boughorbel, 2017, Optimal classifier for imbalanced data using Matthews correlation coefficient metric, PloS one, 12, 10.1371/journal.pone.0177678 Chen, 1992, Fuzzy multiple attribute decision making methods, 289 Davis, 2006, The relationship between Precision-Recall and ROC curves, 233 Demšar, 2006, Statistical comparisons of classifiers over multiple data sets, Journal of Machine Learning Research, 7, 1 Deng, 1982, Control problems of grey systems, Systems & Control Letters, 1, 288, 10.1016/S0167-6911(82)80025-X Fawcett, 2006, An introduction to ROC analysis, Pattern Recognition Letters, 27, 861, 10.1016/j.patrec.2005.10.010 Garcia, 2010, Theoretical analysis of a performance measure for imbalanced data, 617 Halligan, 2015, Disadvantages of using the area under the receiver operating characteristic curve to assess imaging tests: a discussion and proposal for an alternative approach, European Radiology, 25, 932, 10.1007/s00330-014-3487-0 Hand, 2012, Assessing the performance of classification methods, International Statistical Review, 80, 400, 10.1111/j.1751-5823.2012.00183.x Hwang, 1981, Methods for multiple attribute decision making, 58 Hossin, 2015, A review on evaluation metrics for data classification evaluations, International Journal of Data Mining & Knowledge Management Process, 5 He, 2009, Learning from imbalanced data, IEEE Transactions on Knowledge and Data Engineering, 21, 1263, 10.1109/TKDE.2008.239 Jeni, 2013, Facing imbalanced data–recommendations for the use of performance metrics, 245 Kuo, 2008, The use of grey relational analysis in solving multiple attribute decision-making problems, Computers & Industrial Engineering, 55, 80, 10.1016/j.cie.2007.12.002 Kou, 2012, Evaluation of classification algorithms using MCDM and rank correlation, International Journal of Information Technology & Decision Making, 11, 197, 10.1142/S0219622012500095 Koyejo, 2014, Consistent binary classification with generalized performance metrics, 2744 Lin, 2006, The worst ill-conditioned silicon wafer slicing machine detected by using grey relational analysis, The International Journal of Advanced Manufacturing Technology, 31, 388, 10.1007/s00170-006-0685-1 Luque, 2019, The impact of class imbalance in classification performance metrics based on the binary confusion matrix, Pattern Recognition, 91, 216, 10.1016/j.patcog.2019.02.023 Matthews, 1975, Comparison of the predicted and observed secondary structure of T4 phage lysozyme, Biochimica et Biophysica Acta (BBA)-Protein Structure, 405, 442, 10.1016/0005-2795(75)90109-9 Powers, David Martin (2011). Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. Saito, 2015, The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets, PloS One, 10, 10.1371/journal.pone.0118432 Sokolova, 2006, Beyond accuracy, F-score and ROC: a family of discriminant measures for performance evaluation, 1015 Sokolova, 2009, A systematic analysis of performance measures for classification tasks, Information Processing & Management, 45, 427, 10.1016/j.ipm.2009.03.002 Tharwat, 2018, Classification assessment methods, Applied Computing and Informatics, 10.1016/j.aci.2018.08.003 Yin, 2013, Fifteen years of grey system theory research: a historical review and bibliometric analysis, Expert Systems with Applications, 40, 2767, 10.1016/j.eswa.2012.11.002 Zhu, 2017, An empirical comparison of techniques for the class imbalance problem in churn prediction, Information Sciences, 408, 84, 10.1016/j.ins.2017.04.015 Zou, Kelly H. (2002). Receiver operating characteristic (ROC) literature research. On-line bibliography available from: http://splweb.bwh.harvard.edu8000.